Despite much research progress of a method of learning based on imitation of actual human behaviors in a conventional art, learning a biped behavior from motion capture data still has a problem when the behavior requires subtle control for maintaining balance, which is difficult to capture from stored motion data.
Also, there is a problem due to physical imprecision of the captured motion data. Specifically, since a dynamic character model is drastically simplified from an actual human, any biped character which exactly follows captured joint angle trajectories loses its balance and falls over in a few steps.